Metabolomics as a Driver in Advancing Precision Medicine in Sepsis

Derivative spectrophotometry-assisted determination of tryptophan metabolites emerges host and intestinal flora dysregulations during sepsis

Sepsis is a life-threatening condition characterized by organ dysfunction resulting from a dysregulated host response to infection. Dysregulated tryptophan (TRP) metabolites serve as significant indicators for endogenous immune turnovers and abnormal metabolism in the intestinal microbiota during sepsis. Therefore, a high coverage determination of TRP and its metabolites in sepsis is beneficial for the diagnosis and prognosis of sepsis, as well as for understanding the underlying mechanism of sepsis development. However, similar structures in TRP metabolites make it challenging for separation and metabolite identification. Here, high-performance liquid chromatography coupled with a diode array detector (HPLC-DAD) was developed to determine TRP metabolites in rat serum. The first-order derivative spectrophotometry of targeted metabolites in the serum was investigated and proved to be promising for chromatographic peak annotation across different columns and systems. The established method separating the targeted metabolites was optimized and validated to be sensitive and accurate. Application of the method revealed dysregulated TRP metabolites, associated with immune disorders and NAD + metabolism in both the host and gut flora in septic rats. Our findings indicate that the derivative spectrophotometry-assisted method enhances metabolite identifications for the chromatographic systems based on DAD detectors and holds promise for precision medicine in sepsis.

Metabolic biomarkers of neonatal sepsis: identification using metabolomics combined with machine learning

Background

Sepsis is a common disease associated with neonatal and infant mortality, and for diagnosis, blood culture is currently the gold standard method, but it has a low positivity rate and requires more than 2 days to develop. Meanwhile, unfortunately, the specific biomarkers for the early and timely diagnosis of sepsis in infants and for the determination of the severity of this disease are lacking in clinical practice.

Methods

Samples from 18 sepsis infants with comorbidities, 25 sepsis infants without comorbidities, and 25 infants with noninfectious diseases were evaluated using a serum metabolomics approach based on liquid chromatography‒mass spectrometry (LC‒MS) technology. Differentially abundant metabolites were screened via multivariate statistical analysis. In addition, least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses were conducted to identify the key metabolites in infants with sepsis and without infections. The random forest algorithm was applied to determine key differentially abundant metabolites between sepsis infants with and without comorbidities. Receiver operating characteristic (ROC) curves were generated for biomarker value testing. Finally, a metabolic pathway analysis was conducted to explore the metabolic and signaling pathways associated with the identified differentially abundant metabolites.

Results

A total of 189 metabolites exhibited significant differences between infectious infants and noninfectious infants, while 137 distinct metabolites exhibited differences between septic infants with and without comorbidities. After screening for the key differentially abundant metabolites using LASSO and SVM-RFE analyses, hexylamine, psychosine sulfate, LysoPC (18:1 (9Z)/0:0), 2,4,6-tribromophenol, and 25-cinnamoyl-vulgaroside were retained for the diagnosis of infant sepsis. ROC curve analysis revealed that the area under the curve (AUC) was 0.9200 for hexylamine, 0.9749 for psychosine sulfate, 0.9684 for LysoPC (18:1 (9Z)/0:0), 0.7405 for 2,4,6-tribromophenol, 0.8893 for 25-cinnamoyl-vulgaroside, and 1.000 for the combination of all metabolites. When the septic infants with comorbidities were compared to those without comorbidities, four endogenous metabolites with the greatest importance were identified using the random forest algorithm, namely, 12-oxo-20-trihydroxy-leukotriene B4, dihydrovaltrate, PA (8:0/12:0), and 2-heptanethiol. The ROC curve analysis of these four key differentially abundant metabolites revealed that the AUC was 1 for all four metabolites. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and porphyrin metabolism play important roles in infant sepsis.

Conclusion

Serum metabolite profiles were identified, and machine learning was applied to identify the key differentially abundant metabolites in septic infants with comorbidities, septic infants without comorbidities, and infants without infectious diseases. The findings obtained are expected to facilitate the early diagnosis of sepsis in infants and determine the severity of the disease.

Defining sepsis in small animals

OBJECTIVE

To discuss the definitions of sepsis in human and veterinary medicine.

DESIGN

International, multicenter position statement on the need for consensus definitions of sepsis in veterinary medicine.

SETTING

Veterinary private practice and university teaching hospitals.

ANIMALS

Dogs and cats.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Sepsis is a life-threatening condition associated with the body's response to an infection. In human medicine, sepsis has been defined by consensus on 3 occasions, most recently in 2016. In veterinary medicine, there is little uniformity in how sepsis is defined and no consensus on how to identify it clinically. Most publications rely on modified criteria derived from the 1991 and 2001 human consensus definitions. There is a divergence between the human and veterinary descriptions of sepsis and no consensus on how to diagnose the syndrome. This impedes research, hampers the translation of pathophysiology insights to the clinic, and limits our abilities to optimize patient care. It may be time to formally define sepsis in veterinary medicine to help the field move forward. In this narrative review, we present a synopsis of prior attempts to define sepsis in human and veterinary medicine, discuss developments in our understanding, and highlight some criticisms and shortcomings of existing schemes.

CONCLUSIONS

This review is intended to serve as the foundation of current efforts to establish a consensus definition for sepsis in small animals and ultimately generate evidence-based criteria for its recognition in veterinary clinical practice.

Sepsis, Management & Advances in Metabolomics

Though there have been developments in clinical care and management, early and accurate diagnosis and risk stratification are still bottlenecks in septic shock patients. Since septic shock is multifactorial with patient-specific underlying co-morbid conditions, early assessment of sepsis becomes challenging due to variable symptoms and clinical manifestations. Moreover, the treatment strategies are traditionally based on their progression and corresponding clinical symptoms, not personalized. The complex pathophysiology assures that a single biomarker cannot identify, stratify, and describe patients affected by septic shock. Traditional biomarkers like CRP, PCT, and cytokines are not sensitive and specific enough to be used entirely for a patient's diagnosis and prognosis. Thus, the need of the hour is a sensitive and specific biomarker after comprehensive analysis that may facilitate an early diagnosis, prognosis, and drug development. Integration of clinical data with metabolomics would provide means to understand the patient's condition, stratify patients better, and predict the clinical outcome.

Plasma Metabolomics Reveals Distinct Biological and Diagnostic Signatures for Melioidosis

Rationale: The global burden of sepsis is greatest in low-resource settings. Melioidosis, infection with the gram-negative bacterium Burkholderia pseudomallei, is a frequent cause of fatal sepsis in endemic tropical regions such as Southeast Asia. Objectives: To investigate whether plasma metabolomics would identify biological pathways specific to melioidosis and yield clinically meaningful biomarkers. Methods: Using a comprehensive approach, differential enrichment of plasma metabolites and pathways was systematically evaluated in individuals selected from a prospective cohort of patients hospitalized in rural Thailand with infection. Statistical and bioinformatics methods were used to distinguish metabolomic features and processes specific to patients with melioidosis and between fatal and nonfatal cases. Measurements and Main Results: Metabolomic profiling and pathway enrichment analysis of plasma samples from patients with melioidosis (n = 175) and nonmelioidosis infections (n = 75) revealed a distinct immuno-metabolic state among patients with melioidosis, as suggested by excessive tryptophan catabolism in the kynurenine pathway and significantly increased levels of sphingomyelins and ceramide species. We derived a 12-metabolite classifier to distinguish melioidosis from other infections, yielding an area under the receiver operating characteristic curve of 0.87 in a second validation set of patients. Melioidosis nonsurvivors (n = 94) had a significantly disturbed metabolome compared with survivors (n = 81), with increased leucine, isoleucine, and valine metabolism, and elevated circulating free fatty acids and acylcarnitines. A limited eight-metabolite panel showed promise as an early prognosticator of mortality in melioidosis. Conclusions: Melioidosis induces a distinct metabolomic state that can be examined to distinguish underlying pathophysiological mechanisms associated with death. A 12-metabolite signature accurately differentiates melioidosis from other infections and may have diagnostic applications.

Investigating the impact of human blood metabolites on the Sepsis development and progression: a study utilizing two-sample Mendelian randomization

Background

Existing data suggests a potential link between human blood metabolites and sepsis, yet the precise cause-and-effect relationship remains elusive. By using a two-sample Mendelian randomization (MR) analysis, this study aims to establish a causal link between human blood metabolites and sepsis.

Methods

A two-sample MR analysis was employed to investigate the relationship between blood metabolites and sepsis. To assess the causal connection between sepsis and human blood metabolites, five different MR methods were employed, A variety of sensitivity analyses were conducted, including Cochrane's Q test, MR-Egger intercept test, MR-PRESSO and leave-one-out (LOO) analysis. In order to ensure the robustness of the causal association between exposure and outcome, the Bonferroni adjustment was employed. Additionally, we conducted analyses of the metabolic pathways of the identified metabolites using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Small Molecule Pathway Database (SMPDB) database.

Results

The MR analysis revealed a total of 27 metabolites (16 known and 11 unknown) causally linked to the development and progression of sepsis. After applying the Bonferroni correction, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF) remained significant in relation to 28-day all-cause mortality in sepsis. By pathway enrichment analysis, we identified four significant metabolic pathways. Notably, the Alpha Linolenic Acid and Linoleic Acid metabolism pathway emerged as a pivotal contributor to the occurrence and progression of sepsis.

Conclusion

This study provides preliminary evidence of causal associations between human blood metabolites and sepsis, as ascertained by MR analysis. The findings offer valuable insights into the pathogenesis of sepsis and may provide insight into preventive and therapeutic approaches.

Sympathetic nervous activation, mitochondrial dysfunction and outcome in acutely decompensated cirrhosis: the metabolomic prognostic models (CLIF-C MET)

BACKGROUND AND AIMS

Current prognostic scores of patients with acutely decompensated cirrhosis (AD), particularly those with acute-on-chronic liver failure (ACLF), underestimate the risk of mortality. This is probably because systemic inflammation (SI), the major driver of AD/ACLF, is not reflected in the scores. SI induces metabolic changes, which impair delivery of the necessary energy for the immune reaction. This investigation aimed to identify metabolites associated with short-term (28-day) death and to design metabolomic prognostic models.

METHODS

Two prospective multicentre large cohorts from Europe for investigating ACLF and development of ACLF, CANONIC (discovery, n=831) and PREDICT (validation, n=851), were explored by untargeted serum metabolomics to identify and validate metabolites which could allow improved prognostic modelling.

RESULTS

Three prognostic metabolites strongly associated with death were selected to build the models. 4-Hydroxy-3-methoxyphenylglycol sulfate is a norepinephrine derivative, which may be derived from the brainstem response to SI. Additionally, galacturonic acid and hexanoylcarnitine are associated with mitochondrial dysfunction. Model 1 included only these three prognostic metabolites and age. Model 2 was built around 4-hydroxy-3-methoxyphenylglycol sulfate, hexanoylcarnitine, bilirubin, international normalised ratio (INR) and age. In the discovery cohort, both models were more accurate in predicting death within 7, 14 and 28 days after admission compared with MELDNa score (C-index: 0.9267, 0.9002 and 0.8424, and 0.9369, 0.9206 and 0.8529, with model 1 and model 2, respectively). Similar results were found in the validation cohort (C-index: 0.940, 0.834 and 0.791, and 0.947, 0.857 and 0.810, with model 1 and model 2, respectively). Also, in ACLF, model 1 and model 2 outperformed MELDNa 7, 14 and 28 days after admission for prediction of mortality.

CONCLUSIONS

Models including metabolites (CLIF-C MET) reflecting SI, mitochondrial dysfunction and sympathetic system activation are better predictors of short-term mortality than scores based only on organ dysfunction (eg, MELDNa), especially in patients with ACLF.

Predictive value of presepsin and acylcarnitines for severity and biliary drainage in acute cholangitis

BACKGROUND

Bacteremia, which is a major cause of mortality in patients with acute cholangitis, induces hyperactive immune response and mitochondrial dysfunction. Presepsin is responsible for pathogen recognition by innate immunity. Acylcarnitines are established mitochondrial biomarkers.

AIM

To clarify the early predictive value of presepsin and acylcarnitines as biomarkers of severity of acute cholangitis and the need for biliary drainage.

METHODS

Of 280 patients with acute cholangitis were included and the severity was stratified according to the Tokyo Guidelines 2018. Blood presepsin and plasma acylcarnitines were tested at enrollment by chemiluminescent enzyme immunoassay and ultra-high-performance liquid chromatography-mass spectrometry, respectively.

RESULTS

The concentrations of presepsin, procalcitonin, short- and medium-chain acylcarnitines increased, while long-chain acylcarnitines decreased with the severity of acute cholangitis. The areas under the receiver operating characteristic curves (AUC) of presepsin for diagnosing moderate/severe and severe cholangitis (0.823 and 0.801, respectively) were greater than those of conventional markers. The combination of presepsin, direct bilirubin, alanine aminotransferase, temperature, and butyryl-L-carnitine showed good predictive ability for biliary drainage (AUC: 0.723). Presepsin, procalcitonin, acetyl-L-carnitine, hydroxydodecenoyl-L-carnitine, and temperature were independent predictors of bloodstream infection. After adjusting for severity classification, acetyl-L-carnitine was the only acylcarnitine independently associated with 28-d mortality (hazard ratio 14.396; P < 0.001) (AUC: 0.880). Presepsin concentration showed positive correlation with direct bilirubin or acetyl-L-carnitine.

CONCLUSION

Presepsin could serve as a specific biomarker to predict the severity of acute cholangitis and need for biliary drainage. Acetyl-L-carnitine is a potential prognostic factor for patients with acute cholangitis. Innate immune response was associated with mitochondrial metabolic dysfunction in acute cholangitis.

Sustained Perturbation of Metabolism and Metabolic Subphenotypes Are Associated With Mortality and Protein Markers of the Host Response

Perturbed host metabolism is increasingly recognized as a pillar of sepsis pathogenesis, yet the dynamic alterations in metabolism and its relationship to other components of the host response remain incompletely understood. We sought to identify the early host-metabolic response in patients with septic shock and to explore biophysiological phenotyping and differences in clinical outcomes among metabolic subgroups.

DESIGN

We measured serum metabolites and proteins reflective of the host-immune and endothelial response in patients with septic shock.

SETTING

We considered patients from the placebo arm of a completed phase II, randomized controlled trial conducted at 16 U.S. medical centers. Serum was collected at baseline (within 24 hr of the identification of septic shock), 24-hour, and 48-hour postenrollment. Linear mixed models were built to assess the early trajectory of protein analytes and metabolites stratified by 28-day mortality status. Unsupervised clustering of baseline metabolomics data was conducted to identify subgroups of patients.

PATIENTS

Patients with vasopressor-dependent septic shock and moderate organ dysfunction that were enrolled in the placebo arm of a clinical trial.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Fifty-one metabolites and 10 protein analytes were measured longitudinally in 72 patients with septic shock. In the 30 patients (41.7%) who died prior to 28 days, systemic concentrations of acylcarnitines and interleukin (IL)-8 were elevated at baseline and persisted at T24 and T48 throughout early resuscitation. Concentrations of pyruvate, IL-6, tumor necrosis factor-α, and angiopoietin-2 decreased at a slower rate in patients who died. Two groups emerged from clustering of baseline metabolites. Group 1 was characterized by higher levels of acylcarnitines, greater organ dysfunction at baseline and postresuscitation (p < 0.05), and greater mortality over 1 year (p < 0.001).

CONCLUSIONS

Among patients with septic shock, nonsurvivors exhibited a more profound and persistent dysregulation in protein analytes attributable to neutrophil activation and disruption of mitochondrial-related metabolism than survivors.

Current Limitations of Staph Infection Diagnostics, and the Role for VOCs in Achieving Culture-Independent Detection

Staphylococci are broadly adaptable and their ability to grow in unique environments has been widely established, but the most common and clinically relevant staphylococcal niche is the skin and mucous membranes of mammals and birds. S. aureus causes severe infections in mammalian tissues and organs, with high morbidities, mortalities, and treatment costs. S. epidermidis is an important human commensal but is also capable of deadly infections. Gold-standard diagnostic methods for staph infections currently rely upon retrieval and characterization of the infectious agent through various culture-based methods. Yet, obtaining a viable bacterial sample for in vitro identification of infection etiology remains a significant barrier in clinical diagnostics. The development of volatile organic compound (VOC) profiles for the detection and identification of pathogens is an area of intensive research, with significant efforts toward establishing breath tests for infections. This review describes the limitations of existing infection diagnostics, reviews the principles and advantages of VOC-based diagnostics, summarizes the analytical tools for VOC discovery and clinical detection, and highlights examples of how VOC biomarkers have been applied to diagnosing human and animal staph infections.

The Metabolomics of Critical Illness

Critical illness is associated with dramatic changes in metabolism driven by immune, endocrine, and adrenergic mediators. These changes involve early activation of catabolic processes leading to increased energetic substrate availability; later on, they are followed by a hypometabolic phase characterized by deranged mitochondrial function. In sepsis and ARDS, these rapid clinical changes are reflected in metabolomic profiles of plasma and other fluids, suggesting that metabolomics could one day be used to assist in the diagnosis and prognostication of these syndromes. Some metabolites, such as lactate, are already in clinical use and define patients with septic shock, a high-mortality subtype of sepsis. Larger-scale metabolomic profiling may ultimately offer a tool to identify subgroups of critically ill patients who may respond to therapy, but further work is needed before this type of precision medicine is readily employed in the clinical setting.

Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead

Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.

Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival

Background

Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and whether these methods improved upon conventional statistical approaches.

Methods

Plasma gas chromatography–liquid chromatography mass spectrometry quantified 411 metabolites measured ≤ 72 h of ICU admission in 60 patients with sepsis at a single center (Brigham and Women’s Hospital, Boston, USA). Seven ML approaches were trained to differentiate survivors from non-survivors. Model performance predicting 28 day mortality was assessed through internal cross-validation, and innate top-feature (metabolite) selection and rankings were compared across the 7 ML approaches and with conventional statistical methods (logistic regression). Metabolites were consensus ranked by a summary, ensemble ML ranking procedure weighing their contribution to mortality risk prediction across multiple ML models.

Results

Median (IQR) patient age was 58 (47, 62) years, 45% were women, and median (IQR) SOFA score was 9 (6, 12). Mortality at 28 days was 42%. The models’ specificity ranged from 0.619 to 0.821. Partial least squares regression-discriminant analysis and nearest shrunken centroids prioritized the greatest number of metabolites identified by at least one other method. Penalized logistic regression demonstrated top-feature results that were consistent with many ML methods. Across the plasma metabolome, the 13 metabolites with the strongest linkage to mortality defined through an ensemble ML importance score included lactate, bilirubin, kynurenine, glycochenodeoxycholate, phenylalanine, and others. Four of these top 13 metabolites (3-hydroxyisobutyrate, indoleacetate, fucose, and glycolithocholate sulfate) have not been previously associated with sepsis survival. Many of the prioritized metabolites are constituents of the tryptophan, pyruvate, phenylalanine, pentose phosphate, and bile acid pathways.

Conclusions

We identified metabolites linked with sepsis survival, some confirming prior observations, and others representing new associations. The application of ensemble ML feature-ranking tools to metabolomic data may represent a promising statistical platform to support biologic target discovery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-022-00445-8.

Diagnosis of Neonatal Sepsis: The Role of Inflammatory Markers

This is a narrative review on the role of biomarkers in the diagnosis of neonatal sepsis. We describe the difficulties to obtain standardized definitions in neonatal sepsis and discuss the limitations of published evidence of cut-off values and their sensitivities and specificities. Maternal risk factors influence the results of inflammatory markers as do gestational age, the time of sampling, the use of either cord blood or neonatal peripheral blood, and some non-infectious causes. Current evidence suggests that the use of promising diagnostic markers such as CD11b, CD64, IL-6, IL-8, PCT, and CRP, either alone or in combination, might enable clinicians discontinuing antibiotics confidently within 24-48 h. However, none of the current diagnostic markers is sensitive and specific enough to support the decision of withholding antibiotic treatment without considering clinical findings. It therefore seems to be justified that antibiotics are often initiated in ill term and especially preterm infants. Early markers like IL-6 and later markers like CRP are helpful in the diagnosis of neonatal sepsis considering the clinical aspect of the neonate, the gestational age, maternal risk factors and the time (age of the neonate regarding early-onset sepsis) of blood sampling.

Multi-omics strategies for personalized and predictive medicine: past, current, and future translational opportunities

Precision medicine is driven by the paradigm shift of empowering clinicians to predict the most appropriate course of action for patients with complex diseases and improve routine medical and public health practice. It promotes integrating collective and individualized clinical data with patient specific multi-omics data to develop therapeutic strategies, and knowledgebase for predictive and personalized medicine in diverse populations. This study is based on the hypothesis that understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic and predictive biomarkers and optimal paths providing personalized care for diverse and targeted chronic, acute, and infectious diseases. This study briefs emerging significant, and recently reported multi-omics and translational approaches aimed to facilitate implementation of precision medicine. Furthermore, it discusses current grand challenges, and the future need of Findable, Accessible, Intelligent, and Reproducible (FAIR) approach to accelerate diagnostic and preventive care delivery strategies beyond traditional symptom-driven, disease-causal medical practice.

Managing sepsis in the era of precision medicine: challenges and opportunities

INTRODUCTION

Precision medicine is a medical model in which decisions, practices, interventions and therapies are tailored to the individual patient based on their predicted response or risk of disease. Sepsis is a life-threatening condition characterized by immune system dysregulation whose pathophysiology remains incompletely understood. There is much hope that precision medicine can lead to better outcomes in patients with sepsis.

AREAS COVERED

In this review from a comprehensive literature search in PubMed for English-language studies conducted in adults, we highlight recent advances in the diagnosis and treatment of sepsis of bacterial origin in adults using precision medicine approaches including rapid diagnostic tests, predictive biomarkers, genomic methods, rapid antimicrobial susceptibility testing, and monitoring cell mediated immunity. Challenges and directions for future research are also discussed.

EXPERT OPINION

Current diagnostic testing in sepsis relies primarily on conventional cultures (e.g. blood cultures), which are time-consuming and may delay critical therapeutic decisions. Nonculture-based techniques including nucleic acid amplification technologies (NAAT), other molecular methods (biomarkers), and genomic sequencing offer promise to overcome some of the inherent limitations seen with culture-based techniques.

Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.

Gender-specific association of oxidative stress and immune response in septic shock mortality using NMR-based metabolomics

Background: Sepsis and septic shock are still associated with a high mortality rate. The early-stage prediction of septic shock outcomes would be helpful to clinicians for designing their treatment protocol. In addition, it would aid clinicians in patient management by understanding gender disparity in terms of clinical outcomes of septic shock by identifying whether there are sex-based differences in sepsis-associated mortality. Objective: This study aimed to test the hypothesis that gender-based metabolic heterogeneity is associated with sepsis survival and identify the biomarkers of mortality for septic shock in an Indian cohort. Method: The study was performed in an Indian population cohort diagnosed with sepsis/septic shock within 24 hours of admission. The study group was 50 patients admitted to intensive care, comprising 23 females and 27 males. Univariate and multivariate analysis were performed to identify the biomarkers for septic shock mortality and the gender-specific metabolic fingerprint in septic shock-associated mortality. Results: The energy-related metabolites, ketone bodies, choline, and NAG were found to be primarily responsible for differentiating survivors and non-survivors. The gender-based mortality stratification identified a female-specific association of the anti-inflammatory response, innate immune response, and β oxidation, and a male-specific association of the pro-inflammatory response to septic shock. Conclusion: The identified mortality biomarkers may help clinicians estimate the severity of a case, as well as predict the outcome and treatment efficacy. The study underlines that gender is one of the most significant biological factors influencing septic shock metabolomic profiles. This understanding can be utilized to identify novel gender-specific biomarkers and innovative targets relevant for gender medicine.

Immunometabolic signatures predict risk of progression to sepsis in COVID-19

Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986-0.995), with sensitivity of 0.978 (0.963-0.992) and specificity of 0.920 (0.890-0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952-0.977), with sensitivity of 0.993(0.984-1.000) and specificity of 0.851 (0.815-0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800-0.858), with sensitivity of 0.738 (0.695-0.781) and specificity of 0.781 (0.735-0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788-0.874), with sensitivity of 0.765 (0.697-0.832) and specificity of 0.817 (0.770-0.865).

Changes of Lipopolysaccharide-Induced Acute Kidney and Liver Injuries in Rats Based on Metabolomics Analysis

Background

The bacterial endotoxin lipopolysaccharide (LPS) was the classic inducer to establish many inflammatory disease models, especially multiple organ injury. Evidences indicated that the mechanism that causes inflammation response is not just related to cytokine release. The main aim of this study was to better elucidate the possible links between metabolic changes and the pathogenesis of LPS-induced acute liver and kidney in order to understand the mechanisms and screening therapeutic targets for developing early diagnostic strategies and treatments.

Methods

An experimental rat model was established by intraperitoneal injection of 10 mg/kg LPS. An untargeted metabolomics analysis of the serum in the LPS and control groups was carried out using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/QTOF-MS). LPS-induced pathological damage in the lungs, liver, kidneys, and colon was observed, along with changes in biochemical indexes, indicating that there was a severe inflammatory response in many organs after administration of LPS for 8 h. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) showed distinct separation in the serum metabolite profiles between the LPS and control groups, indicating significant changes in endogenous metabolites.

Results

The untargeted metabolomics analysis showed that there were 127 significantly different serum metabolites and 53 altered pathways after LPS administration, including pathways related to the metabolism of D-glutamine and D-glutamate, taurine and hypotaurine, beta-alanine, glutathione, and butanoate, which are involved in the inflammatory response, oxidative stress, and amino acid metabolism.

Conclusion

The study suggested that LPS-induced acute liver and kidney injury mainly involves inflammatory response, oxidative stress, and protein synthesis, finally causing multi-organ damage. Correcting the disturbances to the metabolites and metabolic pathways may help to prevent and/or treat LPS-induced acute liver and kidney damage.

Myristic Acid Serum Levels and Their Significance for Diagnosis of Systemic Inflammatory Response, Sepsis, and Bacteraemia

Myristic acid is identified as a metabolite with the highest diagnostic sensitivity and specificity in the metabolome of patients with bacteraemia. Its significant decrease has been observed in patients with septic shock not responding to treatment. Another study has reported a close correlation of myristic acid levels with the outcome of severe trauma patients. Myristic acid concentrations were investigated in a cohort of septic patients and patients with Systemic Inflammatory Response Syndrome (SIRS) in 5 consecutive days following diagnosis and compared to healthy controls. The study population groups-Sepsis 34, SIRS 31, and Healthy Control 120 patients were included. Serum samples were analyzed using gas chromatography and mass spectrometry. The myristic acid levels in the Sepsis Group and SIRS Group were found to be significantly higher when compared to healthy controls. The serum concentration of myristic acid in septic patients with bacteraemia was higher than in septic patients without bacteraemia. Most patients with sepsis and SIRS had the highest levels of myristic acid within 24 h after an established diagnosis. Myristic acid should be considered as a new candidate marker of severe inflammation and sepsis. A simplified analysis and sufficient body of validated data are necessary steps towards the introduction of this metabolite into routine clinical practice.

Tian-Huang Formula, a Traditional Chinese Medicinal Prescription, Improves Hepatosteatosis and Glucose Intolerance Targeting AKT-SREBP Nexus in Diet-Induced Obese Rats

The progressive increase of metabolic diseases underscores the necessity for developing effective therapies. Although we found Tian-Huang formula (THF) could alleviate metabolic disorders, the underlying mechanism remains to be fully understood. In the present study, firstly, male Sprague-Dawley rats were fed with high-fat diet plus high-fructose drink (HFF, the diet is about 60% of calories from fat and the drink is 12.5% fructose solution) for 14 weeks to induce hepatosteatosis and glucose intolerance and then treated with THF (200 mg/kg) for 4 weeks. Then, metabolomics analysis was performed with rat liver samples and following the clues illustrated by Ingenuity Pathway Analysis (IPA) with the metabolomics discoveries, RT-qPCR and Western blotting were carried out to validate the putative pathways. Our results showed that THF treatment reduced the body weight from 735.1 ± 81.29 to 616.3 ± 52.81 g and plasma triglyceride from 1.5 ± 0.42 to 0.88 ± 0.33 mmol/L; meanwhile, histological examinations of hepatic tissue and epididymis adipose tissue showed obvious alleviation. Compared with the HFF group, the fasting serum insulin and blood glucose level of the THF group were improved from 20.77 ± 6.58 to 9.65 ± 5.48 mIU/L and from 8.96 ± 0.56 to 7.66 ± 1.25 mmol/L, respectively, so did the serum aspartate aminotransferase, insulin resistance index, and oral glucose tolerance (p = 0.0019, 0.0053, and 0.0066, respectively). Furthermore, based on a list of 32 key differential endogenous metabolites, the molecular networks generated by IPA suggested that THF alleviated glucose intolerance and hepatosteatosis by activating phosphatidylinositol-3 kinase (PI3K) and low-density lipoprotein receptor (LDL-R) involved pathways. RT-qPCR and Western blotting results confirmed that THF alleviated hepatic steatosis and glucose intolerance partly through protein kinase B- (AKT-) sterol regulatory element-binding protein (SREBP) nexus. Our findings shed light on molecular mechanisms of THF on alleviating metabolic diseases and provided further evidence for developing its therapeutic potential.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

Estrogen Deprivation and Myocardial Infarction: Role of Aerobic Exercise Training, Inflammation and Metabolomics

In general, postmenopausal women present higher mortality, and worse prognosis after myocardial infarction (MI) compared to men, due to estrogen deficiency. After MI, cardiovascular alterations occur such as the autonomic imbalance and the pro-inflammatory cytokines increase. In this sense, therapies that aim to minimize deleterious effects caused by myocardial ischemia are important. Aerobic training has been proposed as a promising intervention in the prevention of cardiovascular diseases. On the other hand, some studies have attempted to identify potential biomarkers for cardiovascular diseases or specifically for MI. For this purpose, metabolomics has been used as a tool in the discovery of cardiovascular biomarkers. Therefore, the objective of this work is to discuss the changes involved in ovariectomy, myocardial infarction, and aerobic training, with emphasis on inflammation and metabolism.

Systems Biology and Biomarkers in Necrotizing Soft Tissue Infections

In necrotizing soft tissue infection (NSTI) there is a need to identify biomarker sets that can be used for diagnosis and disease management. The INFECT study was designed to obtain such insights through the integration of patient data and results from different clinically relevant experimental models by use of systems biology approaches. This chapter describes the current state of biomarkers in NSTI and how biomarkers are categorized. We introduce the fundamentals of top-down systems biology approaches including analysis tools and we review the use of current methods and systems biology approaches to biomarker discover. Further, we discuss how different "omics" signatures (gene expression, protein, and metabolites) from NSTI patient samples can be used to identify key host and pathogen factors involved in the onset and development of infection, as well as exploring associations to disease outcomes.

L-Carnitine and Acylcarnitines: Mitochondrial Biomarkers for Precision Medicine

Biomarker discovery and implementation are at the forefront of the precision medicine movement. Modern advances in the field of metabolomics afford the opportunity to readily identify new metabolite biomarkers across a wide array of disciplines. Many of the metabolites are derived from or directly reflective of mitochondrial metabolism. L-carnitine and acylcarnitines are established mitochondrial biomarkers used to screen neonates for a series of genetic disorders affecting fatty acid oxidation, known as the inborn errors of metabolism. However, L-carnitine and acylcarnitines are not routinely measured beyond this screening, despite the growing evidence that shows their clinical utility outside of these disorders. Measurements of the carnitine pool have been used to identify the disease and prognosticate mortality among disorders such as diabetes, sepsis, cancer, and heart failure, as well as identify subjects experiencing adverse drug reactions from various medications like valproic acid, clofazimine, zidovudine, cisplatin, propofol, and cyclosporine. The aim of this review is to collect and interpret the literature evidence supporting the clinical biomarker application of L-carnitine and acylcarnitines. Further study of these metabolites could ultimately provide mechanistic insights that guide therapeutic decisions and elucidate new pharmacologic targets.

Acute lung injury - from pathophysiology to treatment

Acute lung injury is characterized by acute respiratory insufficiency with tachypnea, cyanosis refractory to oxygen, decreased lung compliance, and diffuse alveolar infiltrates on chest X-ray. The 1994 American-European Consensus Conference defined "acute respiratory distress syndrome, ARDS" by acute onset after a known trigger, severe hypoxemia defined by PaO2/FiO2</=200 mm Hg, bilateral infiltrates on chest X-ray, and absence of cardiogenic edema. Milder form of the syndrome with PaO2/FiO2 between 200-300 mm Hg was named "acute lung injury, ALI". Berlin Classification in 2012 defined three categories of ARDS according to hypoxemia (mild, moderate, and severe), and the term "acute lung injury" was assigned for general description or for animal models. ALI/ARDS can originate from direct lung triggers such as pneumonia or aspiration, or from extrapulmonary reasons such as sepsis or trauma. Despite growing understanding the ARDS pathophysiology, efficacy of standard treatments, such as lung protective ventilation, prone positioning, and neuromuscular blockers, is often limited. However, there is an increasing evidence that direct and indirect forms of ARDS may differ not only in the manifestations of alterations, but also in the response to treatment. Thus, individualized treatment according to ARDS subtypes may enhance the efficacy of given treatment and improve the survival of patients.

A Multivariate Metabolomics Method for Estimating Platelet Mitochondrial Oxygen Consumption Rates in Patients with Sepsis

BACKGROUND

Sepsis-induced alterations in mitochondrial function contribute to organ dysfunction and mortality. Measuring mitochondrial function in vital organs is neither feasible nor practical, highlighting the need for non-invasive approaches. Mitochondrial function may be reflected in the concentrations of metabolites found in platelets and whole blood (WB) samples. We proposed to use these as alternates to indirectly estimate platelet mitochondrial oxygen consumption rate (mOCR) in sepsis patients.

METHODS

We determined the relationships between platelet mOCR and metabolites in both platelets and WB, as measured by quantitative 1H-NMR metabolomics. The associations were identified by building multiple linear regression models with stepwise forward-backward variable selection. We considered the models to be significant with an ANOVA test (p-value ≤ 0.05) and a positive predicted-R2.

RESULTS

The differences in adjusted-R2 and ANOVA p-values (platelet adj-R2: 0.836 (0.0003), 0.711 (0.0004) vs. WB adj-R2: 0.428 (0.0079)) from the significant models indicate the platelet models were more associated with platelet mOCR.

CONCLUSIONS

Our data suggest there are groups of metabolites in WB (leucine, acetylcarnitine) and platelets (creatine, ADP, glucose, taurine) that are associated with platelet mOCR. Thus, WB and platelet metabolites could be used to estimate platelet mOCR.

Disposable Paper-on-CMOS Platform for Real-Time Simultaneous Detection of Metabolites

OBJECTIVE

Early stage diagnosis of sepsis without overburdening health services is essential to improving patient outcomes.

METHODS

A fast and simple-to-use platform that combines an integrated circuit with paper microfluidics for simultaneous detection of multiple-metabolites appropriate for diagnostics was presented. Paper based sensors are a primary candidate for widespread deployment of diagnostic or test devices. However, the majority of devices today use a simple paper strip to detect a single marker using the reflectance of light. However, for many diseases such as sepsis, one biomarker is not sufficient to make a unique diagnosis. In this work multiple measurements are made on patterned paper simultaneously. Using laser ablation to fabricate microfluidic channels on paper provides a flexible and direct approach for mass manufacture of disposable paper strips. A reusable photodiode array on a complementary metal oxide semiconductor chip is used as the transducer.

RESULTS

The system measures changes in optical absorbance in the paper to achieve a cost-effective and easily implemented system that is capable of multiple simultaneous assays. Potential sepsis metabolite biomarkers glucose and lactate have been studied and quantified with the platform, achieving sensitivity within the physiological range in human serum.

CONCLUSION

We have detailed a disposable paper-based CMOS photodiode sensor platform for real-time simultaneous detection of metabolites for diseases such as sepsis.

SIGNIFICANCE

A combination of a low-cost paper strip with microfluidic channels and a sensitive CMOS photodiode sensor array makes our platform a robust portable and inexpensive biosensing device for multiple diagnostic tests in many different applications.

Integrated Univariate, Multivariate, and Correlation-Based Network Analyses Reveal Metabolite-Specific Effects on Bacterial Growth and Biofilm Formation in Necrotizing Soft Tissue Infections

Necrotizing soft-tissue infections (NSTIs) have multiple causes, risk factors, anatomical locations, and pathogenic mechanisms. In patients with NSTI, circulating metabolites may serve as a substrate having impact on bacterial adaptation at the site of infection. Metabolic signatures associated with NSTI may reveal the potential to be useful as diagnostic and prognostic markers and novel targets for therapy. This study used untargeted metabolomics analyses of plasma from NSTI patients (n = 34) and healthy (noninfected) controls (n = 24) to identify the metabolic signatures and connectivity patterns among metabolites associated with NSTI. Metabolite-metabolite association networks were employed to compare the metabolic profiles of NSTI patients and noninfected surgical controls. Out of 97 metabolites detected, the abundance of 33 was significantly altered in NSTI patients. Analysis of metabolite-metabolite association networks showed a more densely connected network: specifically, 20 metabolites differentially connected between NSTI and controls. A selected set of significantly altered metabolites was tested in vitro to investigate potential influence on NSTI group A streptococcal strain growth and biofilm formation. Using chemically defined media supplemented with the selected metabolites, ornithine, ribose, urea, and glucuronic acid, revealed metabolite-specific effects on both bacterial growth and biofilm formation. This study identifies for the first time an NSTI-specific metabolic signature with implications for optimized diagnostics and therapies.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Precision medicine in pediatric sepsis

PURPOSE OF REVIEW

Pediatric sepsis is a heterogeneous state associated with significant morbidity and mortality, but treatment strategies are limited. Clinical trials of immunomodulators in sepsis have shown no benefit, despite having a strong biological rationale. There is considerable interest in application of a precision medicine approach to pediatric sepsis to identify patients who are more likely to benefit from targeted therapeutic interventions.

RECENT FINDINGS

Precision medicine requires a clear understanding of the molecular basis of disease. 'Omics data' and bioinformatics tools have enabled identification of endotypes of pediatric septic shock, with corresponding biological pathways. Further, using a multibiomarker-based approach, patients at highest risk of poor outcomes can be identified at disease onset. Enrichment strategies, both predictive and prognostic, may be used to optimize patient selection in clinical trials and identify a subpopulation in whom therapy of interest may be trialed. A bedside-to-bench-to-bedside model may offer clinicians pragmatic tools to aid in decision-making.

SUMMARY

Precision medicine approaches may be used to subclassify, risk-stratify, and select pediatric patients with sepsis who may benefit from new therapies. Application of precision medicine will require robust basic and translational research, rigorous clinical trials, and infrastructure to collect and analyze big data.

Heterogeneity in sepsis: new biological evidence with clinical applications

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2019. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2019. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Altered Metabolic Profile of Triglyceride-Rich Lipoproteins in Gut-Lymph of Rodent Models of Sepsis and Gut Ischemia-Reperfusion Injury

BACKGROUND

Triglyceride-rich lipoproteins are important in dietary lipid absorption and subsequent energy distribution in the body. Their importance in the gut-lymph may have been overlooked in sepsis, the most common cause of critical illness, and in gut ischemia-reperfusion injury, a common feature of many critical illnesses.

AIMS

We aimed to undertake an exploratory study of triglyceride-rich lipoprotein fractions in gut-lymph using untargeted metabolic profiling to identify altered metabolites in sepsis or gut ischemia-reperfusion.

METHODS

The gut-lymph was collected from rodent sham, sepsis, and gut ischemia-reperfusion models. The triglyceride-rich lipoprotein-enriched fractions isolated from the gut-lymph were subjected to a dual metabolomics analysis approach: non-polar metabolite analysis by ultra-high performance liquid chromatography-mass spectrometry and polar metabolite analysis by gas chromatography-mass spectrometry.

RESULTS

The metabolite analysis of gut-lymph triglyceride-rich lipoprotein fractions revealed a significant increase (FDR-adjusted P value < 0.05) in myo-inositol in the sepsis group and monoacylglycerols [(18:1) and (18:2)] in gut ischemia-reperfusion. There were no significantly increased specific metabolites in the lipoprotein-enriched fractions of both sepsis and gut ischemia-reperfusion. In contrast, there was a widespread decrease in multiple lipid species in sepsis (35 out of 190; adjusted P < 0.05), but not in the gut ischemia-reperfusion.

CONCLUSIONS

Increased levels of myo-inositol and monoacylglycerols, and decreased multiple lipid species in the gut-lymph triglyceride-rich lipoprotein fraction could be candidates for new biomarkers and/or involved in the progression of sepsis and gut ischemia-reperfusion pathobiology.

Biomarker Phenotype for Early Diagnosis and Triage of Sepsis to the Pediatric Intensive Care Unit

Early diagnosis and triage of sepsis improves outcomes. We aimed to identify biomarkers that may advance diagnosis and triage of pediatric sepsis. Serum and plasma samples were collected from young children (1–23 months old) with sepsis on presentation to the Pediatric Intensive Care Unit (PICU-sepsis, n = 46) or Pediatric Emergency Department (PED-sepsis, n = 58) and PED-non-sepsis patients (n = 19). Multivariate analysis was applied to distinguish between patient groups. Results were compared to our results for older children (2–17 years old). Common metabolites and protein-mediators were validated as potential biomarkers for a sepsis-triage model to differentiate PICU-sepsis from PED-sepsis in children age 1 month-17 years. Metabolomics in young children clearly separated the PICU-sepsis and PED-sepsis cohorts: sensitivity 0.71, specificity 0.93, and AUROC = 0.90 ± 0.03. Adding protein-mediators to the model did not improve performance. The seven metabolites common to the young and older children were used to create the sepsis-triage model. Validation of the sepsis-triage model resulted in sensitivity: 0.83 ± 0.02, specificity: 0.88 ± 0.05 and AUROC 0.93 ± 0.02. The metabolic-based biomarkers predicted which sepsis patients required care in a PICU versus those that could be safely cared for outside of a PICU. This has potential to inform appropriate triage of pediatric sepsis, particularly in EDs with less experience evaluating children.

Molecular signatures of liver dysfunction are distinct in fungal and bacterial infections in mice

Rationale: The liver is a central organ not only for metabolism but also immune function. Life-threatening infections of both bacterial and fungal origin can affect liver function but it is yet unknown whether molecular changes differ depending on the pathogen. We aimed to determine whether the hepatic host response to bacterial and fungal infections differs in terms of hepatic metabolism and liver function. Methods: We compared murine models of infection, including bacterial peritoneal contamination and infection (PCI), intraperitoneal and systemic C. albicans infection, at 6 and 24 h post-infection, to sham controls. The molecular hepatic host response was investigated by the detection of regulatory modules based on large-scale protein-protein interaction networks and expression data. Topological analysis of these regulatory modules was used to reveal infection-specific biological processes and molecular mechanisms. Intravital microscopy and immunofluorescence microscopy were used to further analyze specific aspects of pathophysiology such as cholestasis. Results: Down-regulation of lipid catabolism and bile acid synthesis was observed after 6 h in all infection groups. Alterations in lipid catabolism were characterized by accumulation of long chain acylcarnitines and defective beta-oxidation, which affected metabolism by 6 h. While PCI led to an accumulation of unconjugated bile acids (BA), C. albicans infection caused accumulation of conjugated BA independent of the route of infection. Hepatic dye clearance and transporter expression revealed reduced hepatic uptake in fungal infections vs. defects in secretion following polybacterial infection. Conclusion: Molecular phenotypes of lipid accumulation and cholestasis allow differentiation between pathogens as well as routes of infection at early stages in mice. Targeted metabolomics could be a useful tool for the profiling of infected/septic patients and the type of pathogen, with subsequent customization and targeting of therapy.

Hypermetabolism and Nutritional Support in Sepsis

BACKGROUND

Surgical metabolism has been a founding field of investigation in surgery without which the boundaries of critical care, trauma, and surgical oncology could not have advanced. Traditionally, understanding the shifts in electrolytes, carbohydrates, fats, and amino acids that could explain the rapidly evolving proteolysis after catabolic stress and tumor growth has been a major focus of research that led to our current approach to maintaining homeostasis over the course of major surgical intervention and injury.

METHOD

Review of the English-language literature.

RESULTS

With the emerging field of inflammation and the discovery of cytokines and chemokines, surgical metabolism has taken a second seat in the surgical research arena. Yet central to all patient management after injury is an understanding of how catabolic stress erodes vital organ function and how current approaches can support metabolism through the most physiologically stressful perturbations known to man, for which there is no evolutionary precedent. Although it is well accepted that unabated proteolysis is not a sustainable physiologic state, in the era of modern medicine, precisely how to manipulate the body nutritionally to drive a recovery-directed immune response remains highly debated. This review incorporates multiple lines of inquiry in surgical metabolism, with a particular focus on sepsis.

CONCLUSION

The changing landscape of previous paradigms in the field is discussed. Finally, how next-generation technology might spark renewed interest in this field among surgical investigators is considered.

Metabolomics in Sepsis and Its Impact on Public Health

Sepsis, with its often devastating consequences for patients and their families, remains a major public health concern that poses an increasing financial burden. Early resuscitation together with the elucidation of the biological pathways and pathophysiological mechanisms with the use of "-omics" technologies have started changing the clinical and research landscape in sepsis. Metabolomics (i.e., the study of the metabolome), an "-omics" technology further down in the "-omics" cascade between the genome and the phenome, could be particularly fruitful in sepsis research with the potential to alter the clinical practice. Apart from its benefit for the individual patient, metabolomics has an impact on public health that extends beyond its applications in medicine. In this review, we present recent developments in metabolomics research in sepsis, with a focus on pneumonia, and we discuss the impact of metabolomics on public health, with a focus on free/libre open source software.

The role of metabolomic markers for patients with infectious diseases: implications for risk stratification and therapeutic modulation

INTRODUCTION

Metabolomics is a rapidly growing area of research. Metabolomic markers can provide information about the interaction of different organ systems, and thereby improve the understanding of physio-pathological processes, disease risk, prognosis and therapy responsiveness in a variety of diseases. Areas covered: In this narrative review of recent clinical studies investigating metabolomic markers in adult patients presenting with acute infectious disease, we mainly focused on patients with sepsis and lower respiratory tract infections. Currently, there is a growing body of literature showing that single metabolites from distinct metabolic pathways, as well as more complex metabolomic signatures are associated with disease severity and outcome in patients with systemic infections. These pathways include, among others, metabolomic markers of oxidative stress, steroid hormone and amino acid pathways, and nutritional markers. Expert commentary: Metabolic profiling has great potential to optimize patient management, to provide new targets for individual therapy and thereby improve survival of patients. At this stage, research mainly focused on the identification of new predictive signatures and less on metabolic determinants to predict treatment response. The transition from observational studies to implementation of novel markers into clinical practice is the next crucial step to prove the usefulness of metabolomic markers in patient care.

Maternal sepsis in the era of genomic medicine

PURPOSE

Maternal sepsis remains one of the leading causes of direct and indirect maternal mortality both in high- and low-income environments. In the last two decades, systems biology approaches, based on '-omics' technologies, have started revolutionizing the diagnosis and management of the septic syndrome. The scope of this narrative review is to present an overview of the basic '-omics' technologies, exemplified by cases relevant to maternal sepsis.

METHODS

Narrative review of the new '-omics' technologies based on a detailed review of the literature.

RESULTS

After presenting the main 'omics' technologies, we discuss their limitations and the need for integrated approaches that encompass research efforts across multiple '-omics' layers in the '-omics' cascade between the genome and the phenome.

CONCLUSIONS

Systems biology approaches are revolutionizing the research landscape in maternal sepsis. There is a need for increased awareness, from the side of health practitioners, as a requirement for the effective implementation of the new technologies in the research and clinical practice in maternal sepsis.